Expression statements are used (mostly interactively) to compute and write a
value, or (usually) to call a procedure (a function that returns no meaningful
result; in Python, procedures return the value None). Other uses of
expression statements are allowed and occasionally useful. The syntax for an
expression statement is:

An expression statement evaluates the expression list (which may be a single
expression).

In interactive mode, if the value is not None, it is converted to a string
using the built-in repr() function and the resulting string is written to
standard output on a line by itself (except if the result is None, so that
procedure calls do not cause any output.)

(See section Primaries for the syntax definitions for the last three
symbols.)

An assignment statement evaluates the expression list (remember that this can be
a single expression or a comma-separated list, the latter yielding a tuple) and
assigns the single resulting object to each of the target lists, from left to
right.

Assignment is defined recursively depending on the form of the target (list).
When a target is part of a mutable object (an attribute reference, subscription
or slicing), the mutable object must ultimately perform the assignment and
decide about its validity, and may raise an exception if the assignment is
unacceptable. The rules observed by various types and the exceptions raised are
given with the definition of the object types (see section The standard type hierarchy).

Assignment of an object to a target list, optionally enclosed in parentheses or
square brackets, is recursively defined as follows.

If the target list is a single target: The object is assigned to that target.

If the target list is a comma-separated list of targets: The object must be an
iterable with the same number of items as there are targets in the target list,
and the items are assigned, from left to right, to the corresponding targets.

If the target list contains one target prefixed with an asterisk, called a
“starred” target: The object must be a sequence with at least as many items
as there are targets in the target list, minus one. The first items of the
sequence are assigned, from left to right, to the targets before the starred
target. The final items of the sequence are assigned to the targets after
the starred target. A list of the remaining items in the sequence is then
assigned to the starred target (the list can be empty).

Else: The object must be a sequence with the same number of items as there
are targets in the target list, and the items are assigned, from left to
right, to the corresponding targets.

Assignment of an object to a single target is recursively defined as follows.

If the target is an identifier (name):

If the name does not occur in a global or nonlocal
statement in the current code block: the name is bound to the object in the
current local namespace.

Otherwise: the name is bound to the object in the global namespace or the
outer namespace determined by nonlocal, respectively.

The name is rebound if it was already bound. This may cause the reference
count for the object previously bound to the name to reach zero, causing the
object to be deallocated and its destructor (if it has one) to be called.

If the target is a target list enclosed in parentheses or in square brackets:
The object must be an iterable with the same number of items as there are
targets in the target list, and its items are assigned, from left to right,
to the corresponding targets.

If the target is an attribute reference: The primary expression in the
reference is evaluated. It should yield an object with assignable attributes;
if this is not the case, TypeError is raised. That object is then
asked to assign the assigned object to the given attribute; if it cannot
perform the assignment, it raises an exception (usually but not necessarily
AttributeError).

Note: If the object is a class instance and the attribute reference occurs on
both sides of the assignment operator, the RHS expression, a.x can access
either an instance attribute or (if no instance attribute exists) a class
attribute. The LHS target a.x is always set as an instance attribute,
creating it if necessary. Thus, the two occurrences of a.x do not
necessarily refer to the same attribute: if the RHS expression refers to a
class attribute, the LHS creates a new instance attribute as the target of the
assignment:

This description does not necessarily apply to descriptor attributes, such as
properties created with property().

If the target is a subscription: The primary expression in the reference is
evaluated. It should yield either a mutable sequence object (such as a list)
or a mapping object (such as a dictionary). Next, the subscript expression is
evaluated.

If the primary is a mutable sequence object (such as a list), the subscript
must yield an integer. If it is negative, the sequence’s length is added to
it. The resulting value must be a nonnegative integer less than the
sequence’s length, and the sequence is asked to assign the assigned object to
its item with that index. If the index is out of range, IndexError is
raised (assignment to a subscripted sequence cannot add new items to a list).

If the primary is a mapping object (such as a dictionary), the subscript must
have a type compatible with the mapping’s key type, and the mapping is then
asked to create a key/datum pair which maps the subscript to the assigned
object. This can either replace an existing key/value pair with the same key
value, or insert a new key/value pair (if no key with the same value existed).

For user-defined objects, the __setitem__() method is called with
appropriate arguments.

If the target is a slicing: The primary expression in the reference is
evaluated. It should yield a mutable sequence object (such as a list). The
assigned object should be a sequence object of the same type. Next, the lower
and upper bound expressions are evaluated, insofar they are present; defaults
are zero and the sequence’s length. The bounds should evaluate to integers.
If either bound is negative, the sequence’s length is added to it. The
resulting bounds are clipped to lie between zero and the sequence’s length,
inclusive. Finally, the sequence object is asked to replace the slice with
the items of the assigned sequence. The length of the slice may be different
from the length of the assigned sequence, thus changing the length of the
target sequence, if the object allows it.

CPython implementation detail: In the current implementation, the syntax for targets is taken to be the same
as for expressions, and invalid syntax is rejected during the code generation
phase, causing less detailed error messages.

WARNING: Although the definition of assignment implies that overlaps between the
left-hand side and the right-hand side are ‘safe’ (for example a,b=b,a
swaps two variables), overlaps within the collection of assigned-to variables
are not safe! For instance, the following program prints [0,2]:

(See section Primaries for the syntax definitions for the last three
symbols.)

An augmented assignment evaluates the target (which, unlike normal assignment
statements, cannot be an unpacking) and the expression list, performs the binary
operation specific to the type of assignment on the two operands, and assigns
the result to the original target. The target is only evaluated once.

An augmented assignment expression like x+=1 can be rewritten as x=x+1 to achieve a similar, but not exactly equal effect. In the augmented
version, x is only evaluated once. Also, when possible, the actual operation
is performed in-place, meaning that rather than creating a new object and
assigning that to the target, the old object is modified instead.

With the exception of assigning to tuples and multiple targets in a single
statement, the assignment done by augmented assignment statements is handled the
same way as normal assignments. Similarly, with the exception of the possible
in-place behavior, the binary operation performed by augmented assignment is
the same as the normal binary operations.

These equivalences assume that __debug__ and AssertionError refer to
the built-in variables with those names. In the current implementation, the
built-in variable __debug__ is True under normal circumstances,
False when optimization is requested (command line option -O). The current
code generator emits no code for an assert statement when optimization is
requested at compile time. Note that it is unnecessary to include the source
code for the expression that failed in the error message; it will be displayed
as part of the stack trace.

Assignments to __debug__ are illegal. The value for the built-in variable
is determined when the interpreter starts.

Deletion is recursively defined very similar to the way assignment is defined.
Rather than spelling it out in full details, here are some hints.

Deletion of a target list recursively deletes each target, from left to right.

Deletion of a name removes the binding of that name from the local or global
namespace, depending on whether the name occurs in a global statement
in the same code block. If the name is unbound, a NameError exception
will be raised.

Deletion of attribute references, subscriptions and slicings is passed to the
primary object involved; deletion of a slicing is in general equivalent to
assignment of an empty slice of the right type (but even this is determined by
the sliced object).

Changed in version 3.2: Previously it was illegal to delete a name from the local namespace if it
occurs as a free variable in a nested block.

return may only occur syntactically nested in a function definition,
not within a nested class definition.

If an expression list is present, it is evaluated, else None is substituted.

return leaves the current function call with the expression list (or
None) as return value.

When return passes control out of a try statement with a
finally clause, that finally clause is executed before
really leaving the function.

In a generator function, the return statement is not allowed to
include an expression_list. In that context, a bare return
indicates that the generator is done and will cause StopIteration to be
raised.

The yield statement is only used when defining a generator function,
and is only used in the body of the generator function. Using a yield
statement in a function definition is sufficient to cause that definition to
create a generator function instead of a normal function.
When a generator function is called, it returns an iterator known as a generator
iterator, or more commonly, a generator. The body of the generator function is
executed by calling the next() function on the generator repeatedly until
it raises an exception.

When a yield statement is executed, the state of the generator is
frozen and the value of expression_list is returned to next()‘s
caller. By “frozen” we mean that all local state is retained, including the
current bindings of local variables, the instruction pointer, and the internal
evaluation stack: enough information is saved so that the next time next()
is invoked, the function can proceed exactly as if the yield
statement were just another external call.

The yield statement is allowed in the try clause of a
try ... finally construct. If the generator is not
resumed before it is finalized (by reaching a zero reference count or by being
garbage collected), the generator-iterator’s close() method will be
called, allowing any pending finally clauses to execute.

If no expressions are present, raise re-raises the last exception
that was active in the current scope. If no exception is active in the current
scope, a RuntimeError exception is raised indicating that this is an
error.

Otherwise, raise evaluates the first expression as the exception
object. It must be either a subclass or an instance of BaseException.
If it is a class, the exception instance will be obtained when needed by
instantiating the class with no arguments.

The type of the exception is the exception instance’s class, the
value is the instance itself.

A traceback object is normally created automatically when an exception is raised
and attached to it as the __traceback__ attribute, which is writable.
You can create an exception and set your own traceback in one step using the
with_traceback() exception method (which returns the same exception
instance, with its traceback set to its argument), like so:

raiseException("foo occurred").with_traceback(tracebackobj)

The from clause is used for exception chaining: if given, the second
expression must be another exception class or instance, which will then be
attached to the raised exception as the __cause__ attribute (which is
writable). If the raised exception is not handled, both exceptions will be
printed:

continue may only occur syntactically nested in a for or
while loop, but not nested in a function or class definition or
finally clause within that loop. It continues with the next
cycle of the nearest enclosing loop.

When continue passes control out of a try statement with a
finally clause, that finally clause is executed before
really starting the next loop cycle.

Import statements are executed in two steps: (1) find a module, and initialize
it if necessary; (2) define a name or names in the local namespace (of the scope
where the import statement occurs). The statement comes in two
forms differing on whether it uses the from keyword. The first form
(without from) repeats these steps for each identifier in the list.
The form with from performs step (1) once, and then performs step
(2) repeatedly. For a reference implementation of step (1), see the
importlib module.

To understand how step (1) occurs, one must first understand how Python handles
hierarchical naming of modules. To help organize modules and provide a
hierarchy in naming, Python has a concept of packages. A package can contain
other packages and modules while modules cannot contain other modules or
packages. From a file system perspective, packages are directories and modules
are files. The original specification for packages is still available to read,
although minor details have changed since the writing of that document.

Once the name of the module is known (unless otherwise specified, the term
“module” will refer to both packages and modules), searching
for the module or package can begin. The first place checked is
sys.modules, the cache of all modules that have been imported
previously. If the module is found there then it is used in step (2) of import
unless None is found in sys.modules, in which case
ImportError is raised.

If the module is not found in the cache, then sys.meta_path is searched
(the specification for sys.meta_path can be found in PEP 302).
The object is a list of finder objects which are queried in order as to
whether they know how to load the module by calling their find_module()
method with the name of the module. If the module happens to be contained
within a package (as denoted by the existence of a dot in the name), then a
second argument to find_module() is given as the value of the
__path__ attribute from the parent package (everything up to the last
dot in the name of the module being imported). If a finder can find the module
it returns a loader (discussed later) or returns None.

If none of the finders on sys.meta_path are able to find the module
then some implicitly defined finders are queried. Implementations of Python
vary in what implicit meta path finders are defined. The one they all do
define, though, is one that handles sys.path_hooks,
sys.path_importer_cache, and sys.path.

The implicit finder searches for the requested module in the “paths” specified
in one of two places (“paths” do not have to be file system paths). If the
module being imported is supposed to be contained within a package then the
second argument passed to find_module(), __path__ on the parent
package, is used as the source of paths. If the module is not contained in a
package then sys.path is used as the source of paths.

Once the source of paths is chosen it is iterated over to find a finder that
can handle that path. The dict at sys.path_importer_cache caches
finders for paths and is checked for a finder. If the path does not have a
finder cached then sys.path_hooks is searched by calling each object in
the list with a single argument of the path, returning a finder or raises
ImportError. If a finder is returned then it is cached in
sys.path_importer_cache and then used for that path entry. If no finder
can be found but the path exists then a value of None is
stored in sys.path_importer_cache to signify that an implicit,
file-based finder that handles modules stored as individual files should be
used for that path. If the path does not exist then a finder which always
returns None is placed in the cache for the path.

If no finder can find the module then ImportError is raised. Otherwise
some finder returned a loader whose load_module() method is called with
the name of the module to load (see PEP 302 for the original definition of
loaders). A loader has several responsibilities to perform on a module it
loads. First, if the module already exists in sys.modules (a
possibility if the loader is called outside of the import machinery) then it
is to use that module for initialization and not a new module. But if the
module does not exist in sys.modules then it is to be added to that
dict before initialization begins. If an error occurs during loading of the
module and it was added to sys.modules it is to be removed from the
dict. If an error occurs but the module was already in sys.modules it
is left in the dict.

The loader must set several attributes on the module. __name__ is to be
set to the name of the module. __file__ is to be the “path” to the file
unless the module is built-in (and thus listed in
sys.builtin_module_names) in which case the attribute is not set.
If what is being imported is a package then __path__ is to be set to a
list of paths to be searched when looking for modules and packages contained
within the package being imported. __package__ is optional but should
be set to the name of package that contains the module or package (the empty
string is used for module not contained in a package). __loader__ is
also optional but should be set to the loader object that is loading the
module.

If an error occurs during loading then the loader raises ImportError if
some other exception is not already being propagated. Otherwise the loader
returns the module that was loaded and initialized.

When step (1) finishes without raising an exception, step (2) can begin.

The first form of import statement binds the module name in the local
namespace to the module object, and then goes on to import the next identifier,
if any. If the module name is followed by as, the name following
as is used as the local name for the module.

The from form does not bind the module name: it goes through the list
of identifiers, looks each one of them up in the module found in step (1), and
binds the name in the local namespace to the object thus found. As with the
first form of import, an alternate local name can be supplied by
specifying “as localname”. If a name is not found,
ImportError is raised. If the list of identifiers is replaced by a star
('*'), all public names defined in the module are bound in the local
namespace of the import statement.

The public names defined by a module are determined by checking the module’s
namespace for a variable named __all__; if defined, it must be a sequence of
strings which are names defined or imported by that module. The names given in
__all__ are all considered public and are required to exist. If __all__
is not defined, the set of public names includes all names found in the module’s
namespace which do not begin with an underscore character ('_').
__all__ should contain the entire public API. It is intended to avoid
accidentally exporting items that are not part of the API (such as library
modules which were imported and used within the module).

The from form with * may only occur in a module scope. The wild
card form of import — import* — is only allowed at the module level.
Attempting to use it in class or function definitions will raise a
SyntaxError.

When specifying what module to import you do not have to specify the absolute
name of the module. When a module or package is contained within another
package it is possible to make a relative import within the same top package
without having to mention the package name. By using leading dots in the
specified module or package after from you can specify how high to
traverse up the current package hierarchy without specifying exact names. One
leading dot means the current package where the module making the import
exists. Two dots means up one package level. Three dots is up two levels, etc.
So if you execute from.importmod from a module in the pkg package
then you will end up importing pkg.mod. If you execute from..subpkg2importmod from within pkg.subpkg1 you will import pkg.subpkg2.mod.
The specification for relative imports is contained within PEP 328.

A future statement is a directive to the compiler that a particular
module should be compiled using syntax or semantics that will be available in a
specified future release of Python. The future statement is intended to ease
migration to future versions of Python that introduce incompatible changes to
the language. It allows use of the new features on a per-module basis before
the release in which the feature becomes standard.

A future statement must appear near the top of the module. The only lines that
can appear before a future statement are:

the module docstring (if any),

comments,

blank lines, and

other future statements.

The features recognized by Python 3.0 are absolute_import, division,
generators, unicode_literals, print_function, nested_scopes and
with_statement. They are all redundant because they are always enabled, and
only kept for backwards compatibility.

A future statement is recognized and treated specially at compile time: Changes
to the semantics of core constructs are often implemented by generating
different code. It may even be the case that a new feature introduces new
incompatible syntax (such as a new reserved word), in which case the compiler
may need to parse the module differently. Such decisions cannot be pushed off
until runtime.

For any given release, the compiler knows which feature names have been defined,
and raises a compile-time error if a future statement contains a feature not
known to it.

The direct runtime semantics are the same as for any import statement: there is
a standard module __future__, described later, and it will be imported in
the usual way at the time the future statement is executed.

The interesting runtime semantics depend on the specific feature enabled by the
future statement.

Note that there is nothing special about the statement:

import__future__[asname]

That is not a future statement; it’s an ordinary import statement with no
special semantics or syntax restrictions.

Code compiled by calls to the built-in functions exec() and compile()
that occur in a module M containing a future statement will, by default,
use the new syntax or semantics associated with the future statement. This can
be controlled by optional arguments to compile() — see the documentation
of that function for details.

A future statement typed at an interactive interpreter prompt will take effect
for the rest of the interpreter session. If an interpreter is started with the
-i option, is passed a script name to execute, and the script includes
a future statement, it will be in effect in the interactive session started
after the script is executed.

The global statement is a declaration which holds for the entire
current code block. It means that the listed identifiers are to be interpreted
as globals. It would be impossible to assign to a global variable without
global, although free variables may refer to globals without being
declared global.

Names listed in a global statement must not be used in the same code
block textually preceding that global statement.

Names listed in a global statement must not be defined as formal
parameters or in a for loop control target, class
definition, function definition, or import statement.

CPython implementation detail: The current implementation does not enforce the latter two restrictions, but
programs should not abuse this freedom, as future implementations may enforce
them or silently change the meaning of the program.

Programmer’s note: the global is a directive to the parser. It
applies only to code parsed at the same time as the global statement.
In particular, a global statement contained in a string or code
object supplied to the built-in exec() function does not affect the code
block containing the function call, and code contained in such a string is
unaffected by global statements in the code containing the function
call. The same applies to the eval() and compile() functions.

The nonlocal statement causes the listed identifiers to refer to
previously bound variables in the nearest enclosing scope. This is important
because the default behavior for binding is to search the local namespace
first. The statement allows encapsulated code to rebind variables outside of
the local scope besides the global (module) scope.

Names listed in a nonlocal statement, unlike to those listed in a
global statement, must refer to pre-existing bindings in an
enclosing scope (the scope in which a new binding should be created cannot
be determined unambiguously).

Names listed in a nonlocal statement must not collide with
pre-existing bindings in the local scope.